· Experience taking projects from scoping requirements through V1 launch and V2 iterations.
· Knowledge of professional software engineering practices and best practices for the full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations.
· Experience with highly distributed, multi-tenet systems with clear state-full/state-less boundaries.
· Experience with machine learning, deep learning, data mining, and/or statistical analysis tools.
· Proficiency designing SDKs, frameworks, and working with data science frameworks such as Numpy, MxNet, Tensorflow, etc.
· Passion and experience for mechanical sympathy and performance engineering - in particular using GPGPUs.
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